How effective is financial development in renewable energy investments? Empirical evidence from E−7 countries

Abstract

Today, the world is in the middle of an energy transformation. On the one hand, consumers demand clean energy, and on the other hand, manufacturers are willing to invest in this field. In this context, this study aims to empirically examine the impact of financial development on renewable energy investments in E−7 countries in the 2000–2017 period with the panel threshold regression model developed by Hansen (1999). In addition, the study examined the effects of GDP, patent applications, carbon emissions, inflation, fossil fuel consumption, and the policy index created by the Author as control variables on renewable energy investments. As a result of the analysis, strong evidence was found that the relationship between financial development and renewable energy investments is nonlinear, and there is a single threshold value for financial development (0.3602). However, when looking at the size of the coefficients showing the marginal effects, the positive effect of the increase in financial development on renewable energy investments was found to be above the threshold value (0.8573) and below the threshold value (1.3125). This result shows that the positive marginal effect of financial development on renewable energy investments tends to decrease above the threshold value. This result is thought to be because although the amount of funds in the financial system increased in the later stages of financial development, these funds remained idle and could not be directed to renewable energy investments at the same rate as the level of increase in financial development. In other words, with the development of the financial system, an imbalance may occur among renewable energy investments in the E−7 country group. Kao Panel Cointegration, FMOLS, and DOLS methods were also used in the study to investigate the consistency of the results obtained in the Panel Threshold Regression model. The Panel Threshold Regression analysis concluded that GDP, patent applications, carbon emissions, inflation, and policy index had a significant and positive impact. At the same time, fossil fuel consumption negatively affected renewable energy investments. FMOLS and DOLS results used as alternative models also gave similar results to the panel threshold value model, except for carbon emissions and fossil fuel consumption.